The Fallacy of AI Dominance and the Surrender of Democratic Power
During a September 2026 visit to Ireland, President Donald Trump declared, “We’re leading China in AI [artificial intelligence]. We’re the most sophisticated country in the world, and frankly I want to keep it that way because whoever wins AI wins.” His remarks arrived after months of calls from the public and tech industry insiders to slow AI development. These concerns were triggered by revelations that foundational models from Anthropic, Gemini, Meta, and OpenAI had bypassed safety protocols, accessed networks without authorization, and carried out illicit intrusions. These revelations fueled public panic that tech firms had created superintelligence—an AI exceeding human capability that posed an existential threat to humanity—even though no such breakthrough had actually been achieved.
Public concern intensified in October 2026 when cybersecurity firm Wiz revealed it had used AI tools from Google and OpenAI to identify critical security flaws in PHP: the programming language powering roughly 70% of the web. Although developers quickly released a patch, once the vulnerability was made public hacking attempts surged. In response, the governments of the Netherlands, France, Denmark, and Finland temporarily took several official websites offline.
Widespread panic over AI yielded little legislative action, as lawmakers refused to regulate or tax the industry out of fear that doing so would handicap domestic innovation and yield ground to China. However, the core threat to human existence lies neither in a lost geopolitical race nor in muted technological growth, but rather in the ubiquitous rollout of non-autonomous systems falsely hailed as artificial intelligence.
Techno-utopianism & Deregulation
Big Tech was built on state-funded innovation, with core technologies like the internet, Global Positioning Systems (GPS), and touchscreen displays originating in public institutions. Yet during the deregulation and privatization waves of the 1980s and 1990s, lawmakers sheltered these emerging tech monopolies through minimal taxation and oversight. Most notable was Section 230 of the Communications Decency Act, which insulates platforms from liability for content posted by third parties. Without this protection, social media as we know it would cease to exist. Section 230 absolves tech firms of responsibility for architectures that foster misinformation, even as research confirms that the platforms themselves, not just user posts, are responsible for accelerating the spread of falsehoods over truth.
Lawmakers’ opposition to regulation is rooted in techno-utopianism, the ideological premise that technological progress inherently benefits society. Lawmakers operated under the assumption that any taxation or regulatory oversight would stifle innovation and ultimately harm consumers. Indeed, in 1997, then-President Bill Clinton wrote in an Executive Order “governments attempts to establish technical standards to govern the Internet would only risk inhibiting technological innovation.”
Without meaningful regulation, Big Tech rapidly consolidated into lucrative monopolies—collectively known as FAANG (Facebook, Apple, Amazon, Netflix, and Google) or GAMMA (Google (Alphabet), Apple, Meta (formerly Facebook), Microsoft, and Amazon) conglomerates. Their vast wealth is powered by surveillance capitalism: an economic model that treats human experience as free raw material to be extracted, analyzed, and commercialized. Under this economic order, data is systematically mined through “smart” devices—where “smart” is merely a euphemism for active, continuous monitoring, including the collection of biometric data. This wholesale erosion of privacy has proven extraordinarily lucrative for Big Tech. By feeding this extracted data into algorithms, these firms build detailed psychographic profiles on users and sell the insights to insurance companies determining coverage premiums, employers screening job applicants, and law enforcement agencies evaluating security threats.
Absent meaningful government oversight, Big Tech has been left to police itself. Take the moral panic over fake news after the 2016 Presidential Election, when politicians warned that election meddling in the form of disinformation online was harming a defining feature of the U.S. experiment: democracy. One would think such a realization would prompt serious regulation to protect democratic processes. Rather than holding tech companies accountable for the harm caused by online misinformation, lawmakers have routinely refrained from imposing legal liability. Instead, both parties have resorted to back-channel requests for content removal—Democrats following the January 6 insurrection, and Republicans following Charlie Kirk’s assassination.
Congressional inaction on tech has persisted into the AI era. As of October 2026, 74% of Americans favor stricter AI regulation, yet—with the exception of a few lawmakers like Senator Bernie Sanders—Congress largely opposes intervention. For instance, when OpenAI’s agents bypassed engineers in 2026 to unlawfully access the internet and hack Hugging Face, Representative Jodey Arrington (R-TX) cautioned against regulation, arguing that Congress should be “erring on the side of innovation.” Similarly, when asked about his interest in regulating AI, Representative Chip Roy (R-TX) replied, “I don’t want to regulate anything, I’m a free market conservative.”
China: The Red Herring
Territory of American Canada
To stifle the growing demand for regulation, techno-utopians warned that slowing down AI development would allow China to win the AI race. In September 2026, Anthropic CEO Dario Amodei said that the “toughest dilemma” about his proposal to slow the advancement of AI is that it will not work if China does not do the same. Lawmakers echoed this sentiment with House Speaker Mike Johnson explaining that “We cannot have a moratorium on the development of AI… Because then we will lose our edge to China, and that has serious national security implications for every American family.”
The claim that the U.S. will “fall behind” China by enacting regulations rests on a series of flawed assumptions. First, techno-utopians presume that Big Tech firms are inherently patriotic American entities. In reality, these multinational corporations are neither strictly U.S.-owned nor bound by allegiance to the U.S. Second, it assumes that slowing AI development inherently harms the U.S. and advantages China. Yet critics within China actually oppose a slowdown for the opposite reason: they view it as a tactical maneuver to entrench U.S. market dominance rather than a sincere effort to safeguard humanity.
Moreover, the two nations are pursuing AI development along entirely different trajectories. The Council on Foreign Relations reports that while China excels in research volume, open-weight model accessibility, cost-efficient deployment, and integration into physical manufacturing and robotics, the United States dominates proprietary frontier models, private capital investment, and massive compute infrastructure aimed at developing an AI system with a level of intelligence equal to humans known as Artificial General Intelligence (AGI).
Chasing The AGI Unicorn
U.S. tech companies face a core crisis that has nothing to do with Chinese competition: they have hinged their financial survival on achieving AGI. Yet, today’s AI is far from human intelligence—it is merely a framework of large language models designed to process data and predict text. When a model outputs “4” in response to “2+2=”, it is not performing arithmetic; it is simply selecting the most statistically probable next character.
While this text prediction often creates the illusion of intelligence, the reality is that these systems blindly mirror whatever they are fed and lack any real comprehension. For example, after Elon Musk announced he would train his AI to be less “woke,” the system began spreading baseless, long-discredited white supremacist conspiracy theories. Had the AI been a true, independent critical thinker, it would have used evidence to dispel the falsehoods. Instead, as a mindless prediction system, it simply followed its new directives and amplified the misinformation. The absence of actual reasoning is well-documented: contemporary AI models fail to reliably summarize news stories roughly half the time and routinely invent facts, people, and events. These persistent “hallucinations” reinforce why data journalism professor Meredith Broussard deems the technology “artificial unintelligence,” and why economist Gary Smith calls the race toward AGI the “AI delusion.”
Researchers attempting to construct AGI remain hamstrung by a fundamental obstacle: they cannot agree on what intelligence is. Cognitive scientists long ago determined that human intellect comprises multiple distinct intelligences, a holistic spectrum that artificial systems completely lack. Indeed, AI systems have been documented encouraging suicidal ideation among youth and rationalizing the bombardment of civilian populations, outcomes that any entity possessing emotional intelligence would reject.
The tech sector has insisted that AGI is “right around the corner” since the 1970s, when pioneer Marvin Minsky famously forecasted human-level robot intelligence within three years. Today, however, tech executives press this promise with unprecedented urgency—projecting AGI by 2030—because Big Tech’s financial survival depends on convincing the public, and investors in particular, that breakthrough is imminent. This desperation is driven by the astronomical debt firms have assumed in pursuit of AGI: Anthropic has accumulated $80 billion in debt, while OpenAI owes $665 billion in total economic commitments. The AI industry is essentially propping itself up on a single wager: that its massive debts won’t come due before AGI is achieved. To remain solvent, the sector relies on complex vendor financing mechanisms where tech giants artificially inflate demand by funding their own customer base. A prime example of this circular architecture is Nvidia—the dominant producer of AI microchips—committing $100 billion to OpenAI, even as OpenAI pledged billions toward purchasing chips from rival AMD while simultaneously acquiring an equity stake in the competing hardware maker.
Conclusion: The Real Problem Is Deployment, Not Democracy
China serves as a convenient smoke screen for Big Tech’s financial liabilities and unfulfilled promises. The real danger facing the public is not superintelligent AI, but the widespread deployment of flawed, unintelligent models. For fifty years, lawmakers allowed tech firms to weave their software into the fabric of banking, healthcare, commerce, and legal systems without oversight. As the October 2026 revelations from Wiz about PHP vulnerabilities demonstrated, the rapid digitization of everything created massive security vulnerabilities that nations and institutions are now scrambling to repair.
Rather than fixing this problem, AI has made it worse. The PHP vulnerabilities exposed by Wiz reveal a core contradiction in AI technology: while it can accelerate the identification of security flaws at speeds far beyond human capacity, it remains an unintelligent substitute for human judgment when it comes to engineering secure systems.
The development of AI has done nothing to check the invasion of Big Tech into daily life, and the consequences of deploying unintelligent AI extend far beyond cybersecurity. The widespread adoption of unproven AI has already contributed to botched surgeries in hospitals, a measurable decline in student cognitive abilities within schools, and price-fixing algorithms that artificially inflate rates for renters and consumers at corporations such as McDonald’s. Furthermore, the financial returns promised to enterprises have failed to materialize, with 95% of AI pilot programs ultimately ending in failure.
By surrendering regulatory power to corporate monopolies out of fear of a fictional AGI arms race, society has ceded its democratic control to digital landlords. The threat to human freedom is not a self-aware superintelligence taking over from afar, but our own willing submission to non-autonomous, profit-driven software running the infrastructure of everyday life. Without democratic oversight and civic control, society will remain mere tenants in a digital realm it allowed Big Tech to build and rule.
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Higdon is an author, media critic and lecturer at the University of California, Santa Cruz, whose work explores the intersections of politics, media, technology and education. He is also a co-host of Just Ask the Press, a KTVU political analyst and a national judge for Project Censored. His books include The Anatomy of Fake News and United States of Distraction.
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